The importance, extent, and mode of interspecific gene flow for the evolution of species has long been debated. Characterization of genomic differentiation in a classic example of hybridization between all-black carrion crows and gray-coated hooded crows identified genome-wide introgression extending far beyond the morphological hybrid zone. Gene expression divergence was concentrated in pigmentation genes expressed in gray versus black feather follicles. Only a small number of narrow genomic islands exhibited resistance to gene flow. One prominent genomic region (<2 megabases) harbored 81 of all 82 fixed differences (of 8.4 million single-nucleotide polymorphisms in total) linking genes involved in pigmentation and in visual perception-a genomic signal reflecting color-mediated prezygotic isolation. Thus, localized genomic selection can cause marked heterogeneity in introgression landscapes while maintaining phenotypic divergence.

The global loss of biodiversity continues at an alarming rate. Genomic approaches have been suggested as a promising tool for conservation practice, and we discuss how scaling-up to genome-wide inference can benefit traditional conservation genetic approaches and provide qualitatively novel insights. Yet, the generation of genomic data and subsequent analyses and interpretations are still challenging and largely confined to academic research in ecology and 20evolution. This generates a gap between basic research and applicable solutions for conservation managers faced with multifaceted problems. Before the real-world conservation potential of genomic research can be realized, we suggest that current infrastructures need to be modified, methods must mature, analytical pipelines need to be developed, and successful case studies must be disseminated to practitioners. 3 Conservation biology and genomicsLike most of the life sciences, conservation biology is being confronted with the challenge of how to integrate the collection and analysis of large-scale genomic data into its toolbox. Conservation biologists pull from a wide array of disciplines in an effort to preserve biodiversity and ecosystem services [1]. Genetic data have helped in this regard by 30 detecting, for example, population substructure, measuring genetic connectivity, and identifying potential risks associated with demographic change and inbreeding [2]. Traditionally, conservation genetics (see Glossary) has relied on a handful of molecular markers ranging from a few allozymes to dozens of microsatellites [3]. But for close to a decade [4], genomics -broadly defined high-throughput sampling of nucleic acids [5] -has been touted as an important advancement to the field, a panacea of sorts for the unresolved conservation problems typically addressed 35 with genetic data [6,7]. This transition has led to much promise, but also hyperbole, where concrete empirical examples of genomic data having a conservation impact remain rare.Under the premise that assisting conservation of the world's biota is its ultimate purpose, the emerging field of conservation genomics must openly and pragmatically discuss its potential contribution towards this goal. While there 40are prominent examples where genetic approaches have made inroads influencing conservation efforts (e.g., Florida panther augmentation [8,9]) and wildlife enforcement (i.e., detecting illegal harvest [10]), it is not immediately clear that the conservation community and society more broadly have embraced genomics as a useful tool for conservation.Maintaining genetic diversity has largely been an afterthought when it comes to national biodiversity policies [11,12], and attempts to identify areas that might prove to be essential for conserving biological diversity rarely mention 45 genomics (e.g. [13,14]). An obvious reason for this disconnect is that many of the pressing conservation issues (e.g., [15,16]) simply do not need genomics, but instead need political will.The traditional use of gene...

Marine mammals from different mammalian orders share several phenotypic traits adapted to the aquatic environment and are therefore a classic example of convergent evolution. To investigate convergent evolution at the genomic level, we sequenced and de novo assembled the genomes of three species of marine mammals (the killer whale, walrus and manatee) from three mammalian orders that share independently evolved phenotypic adaptations to a marine existence. Our comparative genomic analyses found that convergent amino acid substitutions were widespread throughout the genome, and that a subset were in genes evolving under positive selection and putatively associated with a marine phenotype. However, we found higher levels of convergent amino acid substitutions in a control set of terrestrial sister taxa to the marine mammals. Our results suggest that while convergent molecular evolution is relatively common, adaptive molecular convergence linked to phenotypic convergence is comparatively rare.

Uncovering the genetic basis of species diversification is a central goal in evolutionary biology. Yet, the link between the accumulation of genomic changes during population divergence and the evolutionary forces promoting reproductive isolation is poorly understood. Here, we analysed 124 genomes of crow populations with various degrees of genome-wide differentiation, with parallelism of a sexually selected plumage phenotype, and ongoing hybridization. Overall, heterogeneity in genetic differentiation along the genome was best explained by linked selection exposed on a shared genome architecture. Superimposed on this common background, we identified genomic regions with signatures of selection specific to independent phenotypic contact zones. Candidate pigmentation genes with evidence for divergent selection were only partly shared, suggesting context-dependent selection on a multigenic trait architecture and parallelism by pathway rather than by repeated single-gene effects. This study provides insight into how various forms of selection shape genome-wide patterns of genomic differentiation as populations diverge.